Uses of Class
edu.umass.cs.mallet.base.types.SparseVector

Packages that use SparseVector

Package	Description
edu.umass.cs.mallet.base.fst
edu.umass.cs.mallet.base.types
edu.umass.cs.mallet.base.util

Uses of SparseVector in edu.umass.cs.mallet.base.fst

Methods in edu.umass.cs.mallet.base.fst that return SparseVector

Modifier and Type	Method and Description
SparseVector[]	CRFByGISUpdate.getWeights()
SparseVector[]	CRF4.getWeights()
SparseVector[]	CRF3.getWeights()
SparseVector	CRFByGISUpdate.getWeights(int weightIndex)
SparseVector	CRF4.getWeights(int weightIndex)
SparseVector	CRF3.getWeights(int weightIndex)
SparseVector	CRF2.getWeights(int weightIndex)
SparseVector	CRFByGISUpdate.getWeights(String weightName)
SparseVector	CRF4.getWeights(String weightName)
SparseVector	CRF3.getWeights(String weightName)
SparseVector	CRF2.getWeights(String weightName)

Methods in edu.umass.cs.mallet.base.fst with parameters of type SparseVector

Modifier and Type	Method and Description
void	CRFByGISUpdate.setWeights(int weightsIndex, SparseVector transitionWeights)
void	CRF4.setWeights(int weightsIndex, SparseVector transitionWeights)
void	CRF3.setWeights(int weightsIndex, SparseVector transitionWeights)
void	CRF2.setWeights(int weightsIndex, SparseVector transitionWeights)
void	CRFByGISUpdate.setWeights(SparseVector[] m)
void	CRF4.setWeights(SparseVector[] m)
void	CRF3.setWeights(SparseVector[] m)
void	CRFByGISUpdate.setWeights(String weightName, SparseVector transitionWeights)
void	CRF4.setWeights(String weightName, SparseVector transitionWeights)
void	CRF3.setWeights(String weightName, SparseVector transitionWeights)
void	CRF2.setWeights(String weightName, SparseVector transitionWeights)

Uses of SparseVector in edu.umass.cs.mallet.base.types

Subclasses of SparseVector in edu.umass.cs.mallet.base.types

Modifier and Type	Class and Description
class	AugmentableFeatureVector
class	ExpGain
class	FeatureCounts
class	FeatureVector A subset of an Alphabet in which each element of the subset has an associated value.
class	GainRatio List of features along with their thresholds sorted in descending order of the ratio of (1) information gained by splitting instances on the feature at its associated threshold value, to (2) the split information.
class	GradientGain
class	HashedSparseVector
class	IndexedSparseVector
class	InfoGain
class	KLGain
class	LabelVector
class	Multinomial A probability distribution over a set of features represented as a FeatureVector.
static class	Multinomial.Logged A Multinomial in which the values associated with each feature index fi is Math.log(probability[fi]) instead of probability[fi].
class	PartiallyRankedFeatureVector
class	RankedFeatureVector

Methods in edu.umass.cs.mallet.base.types that return SparseVector

Modifier and Type	Method and Description
SparseVector	AugmentableFeatureVector.toSparseVector()
SparseVector	SparseVector.vectorAdd(SparseVector v, double scale)

Methods in edu.umass.cs.mallet.base.types with parameters of type SparseVector

Modifier and Type	Method and Description
double	NormalizedDotProductMetric.distance(SparseVector a, int hashCodeA, SparseVector b, int hashCodeB)
double	CachedMetric.distance(SparseVector a, int hashCodeA, SparseVector b, int hashCodeB)
double	NormalizedDotProductMetric.distance(SparseVector a, SparseVector b)
double	Minkowski.distance(SparseVector a, SparseVector b)
double	Metric.distance(SparseVector a, SparseVector b)
double	SparseVector.dotProduct(SparseVector v)
double	IndexedSparseVector.dotProduct(SparseVector v)
double	HashedSparseVector.dotProduct(SparseVector v)
double	AugmentableFeatureVector.dotProduct(SparseVector v)
double	SparseVector.extendedDotProduct(SparseVector v)
void	AugmentableFeatureVector.plusEquals(SparseVector v)
void	AugmentableFeatureVector.plusEquals(SparseVector v, double factor)
void	SparseVector.plusEqualsSparse(SparseVector v) For each index i that is present in this vector, set this[i] += v[i].
void	IndexedSparseVector.plusEqualsSparse(SparseVector v)
void	HashedSparseVector.plusEqualsSparse(SparseVector v)
void	SparseVector.plusEqualsSparse(SparseVector v, double factor) For each index i that is present in this vector, set this[i] += factor * v[i].
void	IndexedSparseVector.plusEqualsSparse(SparseVector v, double factor)
void	HashedSparseVector.plusEqualsSparse(SparseVector v, double factor)
void	SparseVector.timesEqualsSparse(SparseVector v) For each index i that is present in this vector, set this[i] *= v[i].
void	SparseVector.timesEqualsSparse(SparseVector v, double factor) For each index i that is present in this vector, set this[i] *= factor * v[i].
SparseVector	SparseVector.vectorAdd(SparseVector v, double scale)

Constructors in edu.umass.cs.mallet.base.types with parameters of type SparseVector

Constructor and Description
PartiallyRankedFeatureVector(Alphabet dict, SparseVector v)
RankedFeatureVector(Alphabet dict, SparseVector v)

Uses of SparseVector in edu.umass.cs.mallet.base.util

Methods in edu.umass.cs.mallet.base.util that return SparseVector

Modifier and Type	Method and Description
static SparseVector	VectorStats.mean(InstanceList instances) Returns a SparseVector whose entries (taken from the union of those in the instances) are the expected values of those in the InstanceList.
static SparseVector	VectorStats.mean(InstanceList instances, int numIndices) Returns a SparseVector whose entries (dense with the given number of indices) are the expected values of those in the InstanceList.
static SparseVector	VectorStats.mean(InstanceList instances, int[] indices) Returns a SparseVector whose entries (the given indices) are the expected values of those in the InstanceList.
static SparseVector	VectorStats.stddev(InstanceList instances) Square root of unbiased variance.
static SparseVector	VectorStats.stddev(InstanceList instances, boolean unbiased) Square root of variance.
static SparseVector	VectorStats.stddev(InstanceList instances, SparseVector mean) Square root of unbiased variance of instances having the given mean
static SparseVector	VectorStats.stddev(InstanceList instances, SparseVector mean, boolean unbiased) Square root of variance.
static SparseVector	VectorStats.variance(InstanceList instances) Returns unbiased variance
static SparseVector	VectorStats.variance(InstanceList instances, boolean unbiased) Returns a SparseVector whose entries (taken from the union of those in the instances) are the variance of those in the InstanceList.
static SparseVector	VectorStats.variance(InstanceList instances, SparseVector mean) Returns unbiased variance of instances having the given mean.
static SparseVector	VectorStats.variance(InstanceList instances, SparseVector mean, boolean unbiased) Returns a SparseVector whose entries (taken from the mean argument) are the variance of those in the InstanceList.

Methods in edu.umass.cs.mallet.base.util with parameters of type SparseVector

Modifier and Type	Method and Description
static SparseVector	VectorStats.stddev(InstanceList instances, SparseVector mean) Square root of unbiased variance of instances having the given mean
static SparseVector	VectorStats.stddev(InstanceList instances, SparseVector mean, boolean unbiased) Square root of variance.
static SparseVector	VectorStats.variance(InstanceList instances, SparseVector mean) Returns unbiased variance of instances having the given mean.
static SparseVector	VectorStats.variance(InstanceList instances, SparseVector mean, boolean unbiased) Returns a SparseVector whose entries (taken from the mean argument) are the variance of those in the InstanceList.